Our customer is a fitness brand with more than 90 locations in the US. In a competitive industry, where customer experience is key, our customer wanted to improve its member check-in experience using facial recognition.
An IoT DeepLens project was initially conceptualized during a conversation with the AWS DeepLens team. Cloudreach was brought in at this stage to create a project plan to build a facial recognition platform leveraging all AWS native services and devices.
The camera system was built leveraging AWS DeepLens with an integrated camera. This was loaded with AWS GreenGrass, complete with a facial detection algorithm leveraging local Machine learning interference and Lambda function execution. The image and customer processing utilized AWS Cloud services including IoT, Lambda, S3, DynamoDB, AWS Rekognition and EC2.
We used Sagemaker build machine learning capabilities to significantly improve image recognition and build intelligent models using member check-in time to the gym.
Cloudreach delivered a facial recognition solution that allows members to seamlessly enter the customer’s locations without interruption.
The custom, facial recognition solution utilized an AWS DeepLens camera with facial recognition algorithm on-device, to check-in known members as they pass the camera. A custom front-end displayed the images captured for manual verification and member identification when recognized.
This solution also provided front desk personnel with information about members as they entered the gym. This allowed the customer to further enhance the member experience with positive, personalized greetings.
In addition, the customer wanted to be able to analyze the sentiment of customers during the process, made possible using AWS Rekognition. This allows them to better understand the mood of their members providing more data that can be used to tailor the perks and discounts on offer to the customer when they are using the gym’s facilities.